SIPLAB: Sensing, Interaction & Perception Lab

In the SIPLAB at ETH Zürich, we're a cross-disciplinary research group in computational interaction, embodied perception, and mobile health. Our work spans human-computer interaction, mixed reality, and machine learning. We are part of the Department of Computer Science, affiliated with the Department of Information Technology & Electrical Engineering, and HCI@ETH.

egocentric multimodal tracking scalable methods for action & motion capture
computational interaction decoding embodied input for situated adaptive systems
predictive mobile health signal processing for physiological data in the wild

Projects to appear and recent research

JMIR Neurotechnology 2024

The Autonomic Nervous System drives Sleep Quality

Sleep Quality Estimation in Multiple Sclerosis Patients
ACM SIGGRAPH 2024

Ultra Inertial Poser

Scalable Motion Capture and Tracking from Sparse Inertial Sensors and Ultra-Wideband Ranging
IEEE EMBC 2024

Multi-Site Photoplethysmography

Robust heart rate detection via multi-site signal fusion
IEEE EMBC 2024

Unsupervised Sleep Quality Estimation

Learning Cardiac Activity for Predicting Sleep Quality
PLOS ONE 2024

Predicting Perceived Sleep Quality

Interpretable Models based on Cardiovascular and Behavioral Features
ACM CUI 2024

Chatbots With Attitude

Enhancing Chatbot Interactions Through Dynamic Personality Infusion
ACM EICS 2024

MARLUI

Multi-Agent Reinforcement Learning for Adaptive Point-and-Click UIs
ACM IMWUT 2024

The Personality Dimensions GPT-3 Expresses During Human-Chatbot Interactions

ACM IMWUT 2024

Detecting Users' Emotional States

Affective State Awareness during Passive Social Media Use
IEEE ICRA 2024

MiBOT

A head-worn robot that modulates cardiovascular responses through human-like soft massage

Affiliations and collaborations

In our projects, we collaborate with faculty and students at the Department of Health Sciences and Technology, the Robotics, Systems and Control (RSC) program at the Department of Mechanical and Process Engineering, and the Faculty of Medicine at University of Zurich.

We are part of ETH's Competence Centre for Rehabilitation Engineering and Science (ETH RESC). We are also affiliated with the ETH AI Center, the Max Planck ETH Center for Learning Systems (CLS), the ELLIS Unit Zürich, and the Zurich Information Security & Privacy Center (ZISC).